测试结构化电子健康记录(EHR)病例审查过程,以识别急性护理中的诊断错误(DE)和诊断过程失败(DPF)。
我们采用了经过验证的工具(更安全的Dx,诊断错误评估研究[DEER]分类法),以评估医院相遇期间的诊断过程,并对13种假定的电子触发因素进行分类。我们创建了两个测试队列,包括所有可预防病例(n=28)和相同数量的随机抽样不可预防病例(n=28),来自365名成年普通药物患者,这些患者过期并接受了我们机构的死亡率病例审查过程。在排除住院时间超过一个月的病人后,每例病例均由两名接受过我们流程培训的盲症临床医师和一个专家小组进行审查.评估者间的可靠性。我们比较了两个队列中DE导致死亡的频率,以及每个队列中DE阳性和阴性病例的平均DPF和电子触发因素。
27例(96.4%)可预防和24例(85.7%)不可预防的病例接受了我们的审查程序。评估者之间的可靠性在个体审稿人之间中等(科恩的kappa0.41),而在专家小组中基本可靠(科恩的kappa0.74)。与不可预防队列相比,可预防队列的DE导致死亡的频率明显更高(56%vs.17%,或6.25[1.68,23.27],p<0.01)。在每个队列中,与DE阴性病例相比,DE阳性的平均DPF和电子触发因素显着升高,而不是显着升高。分别。
使用我们的结构化EHR案例审查流程,我们观察到最终共识和专家小组审查之间的实质性共识。在机构指定的可预防和不可预防的病例中确定了导致与DPF相关的死亡的DEs。虽然电子触发器可能有助于区分DE阳性和DE阴性情况,需要更大规模的研究进行验证。我们的方法有可能增加关于DE监测的机构死亡率病例审查过程。
To test a structured electronic health record (EHR)
case review process to identify diagnostic errors (DE) and diagnostic process failures (DPFs) in acute care.
We adapted validated tools (Safer Dx, Diagnostic Error Evaluation Research [DEER] Taxonomy) to assess the diagnostic process during the hospital encounter and categorized 13 postulated e-triggers. We created two test cohorts of all preventable cases (n=28) and an equal number of randomly sampled non-preventable cases (n=28) from 365 adult general medicine patients who expired and underwent our institution\'s mortality
case review process. After excluding patients with a length of stay of more than one month, each
case was reviewed by two blinded clinicians trained in our process and by an expert panel. Inter-rater reliability was assessed. We compared the frequency of DE contributing to death in both cohorts, as well as mean DPFs and e-triggers for DE positive and negative cases within each cohort.
Twenty-seven (96.4%) preventable and 24 (85.7%) non-preventable cases underwent our review process. Inter-rater reliability was moderate between individual reviewers (Cohen\'s kappa 0.41) and substantial with the expert panel (Cohen\'s kappa 0.74). The frequency of DE contributing to death was significantly higher for the preventable compared to the non-preventable cohort (56% vs. 17%, OR 6.25 [1.68, 23.27], p<0.01). Mean DPFs and e-triggers were significantly and non-significantly higher for DE positive compared to DE negative cases in each cohort, respectively.
We observed substantial agreement among final consensus and expert panel reviews using our structured EHR
case review process. DEs contributing to death associated with DPFs were identified in institutionally designated preventable and non-preventable cases. While e-triggers may be useful for discriminating DE positive from DE negative cases, larger studies are required for validation. Our approach has potential to augment institutional mortality
case review processes with respect to DE surveillance.